The ability for investors and other entities to lend and borrow securities and engage in other types of securities transactions is an important component of a modern global economy.
Unlike sales of many other types of securities, there is no established market or exchange for securities lending transactions. Even when available, market clearing information on the value of a given borrowed security is often incomplete and outdated. As a result, there is no effective benchmark against which individual lending transactions can be compared to ensure that lenders and/or borrowers are achieving optimal value. Moreover, the unavailability and transient nature of securities trading data can be further compounded by the lack of proper analysis tools necessary to process and analyze the data.
In association with lending securities, it is useful to identify preferential arrangements which may consciously or unconsciously exist between certain traders and certain brokers and which might negatively impact optimum pricing levels. Inefficient manual reviews of trades made during a given day, week or other time period are often employed in an attempt to analyze trading activity, to identify anomalous trades and to evaluate the performance of individual traders. However, such manual reviews of trading data are often inadequate to detect potentially inappropriate trader-broker relationships.
In view of these issues, enhanced systems, processes, tools, techniques and strategies are needed for analyzing security trades, including trade data which arise from securities lending transactions.